MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations

• URL: http://arxiv.org/abs/2405.16584v1
• Date: Sun, 26 May 2024 14:27:48 GMT
• Title: MentalManip: A Dataset For Fine-grained Analysis of Mental Manipulation in Conversations
• Authors: Yuxin Wang, Ivory Yang, Saeed Hassanpour, Soroush Vosoughi,
• Abstract summary: Mental manipulation is a significant form of abuse in interpersonal conversations. Our study introduces a new dataset, named $rm Msmall entalMsmall anip$, which consists of $4,000$ annotated movie dialogues. This dataset enables a comprehensive analysis of mental manipulation, pinpointing both the techniques utilized for manipulation and the vulnerabilities targeted in victims.
• Score: 41.661208833153225
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Mental manipulation, a significant form of abuse in interpersonal conversations, presents a challenge to identify due to its context-dependent and often subtle nature. The detection of manipulative language is essential for protecting potential victims, yet the field of Natural Language Processing (NLP) currently faces a scarcity of resources and research on this topic. Our study addresses this gap by introducing a new dataset, named ${\rm M{\small ental}M{\small anip}}$, which consists of $4,000$ annotated movie dialogues. This dataset enables a comprehensive analysis of mental manipulation, pinpointing both the techniques utilized for manipulation and the vulnerabilities targeted in victims. Our research further explores the effectiveness of leading-edge models in recognizing manipulative dialogue and its components through a series of experiments with various configurations. The results demonstrate that these models inadequately identify and categorize manipulative content. Attempts to improve their performance by fine-tuning with existing datasets on mental health and toxicity have not overcome these limitations. We anticipate that ${\rm M{\small ental}M{\small anip}}$ will stimulate further research, leading to progress in both understanding and mitigating the impact of mental manipulation in conversations.

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